RIKEN Center for Advanced Intelligence Project

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合作机构同一篇文章里的其他机构

1. Ton Duc Thang University越南3
2. Duy Tan University越南3
3. University of Technology Sydney澳大利亚3
4. University of Technology Malaysia马来西亚2
5. University of Hafr Al-Batin沙特阿拉伯2
6. Kermanshah University of Technology伊朗2
7. Northern Technical University伊拉克2
8. National Research Institute for Earth Science and Disaster Resilience日本1

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逐年被引

最新文献

1. 1
   Landslide susceptibility mapping based on data mining models in Lesser Caucasus and Kura foreland basin (Armenia and Azerbaijan)Geomatics, Natural Hazards and Risk20252
2. 2
   Evaluating the impact of land use/land cover and rainfall changes on regional soil erosionGeomatics, Natural Hazards and Risk20256
3. 3
   Water depth estimation from Sentinel-2 imagery using advanced machine learning methods and explainable artificial intelligenceGeomatics, Natural Hazards and Risk202335
4. 4
   Brief communication: Radar images for monitoring informal urban settlements in vulnerable zones in Lima, PeruNatural Hazards and Earth System Sciences202213
5. 5
   Predicting PM2.5 levels over the north of Iraq using regression analysis and geographical information system (GIS) techniquesGeomatics, Natural Hazards and Risk202131
6. 6
   Two novel neural-evolutionary predictive techniques of dragonfly algorithm (DA) and biogeography-based optimization (BBO) for landslide susceptibility analysisGeomatics, Natural Hazards and Risk201923
7. 7
   Air quality index prediction using IDW geostatistical technique and OLS-based GIS technique in Kuala Lumpur, MalaysiaGeomatics, Natural Hazards and Risk2019123
8. 8
   Novel hybrids of adaptive neuro-fuzzy inference system (ANFIS) with several metaheuristic algorithms for spatial susceptibility assessment of seismic-induced landslideGeomatics, Natural Hazards and Risk201993
9. 9
   Potential of hybrid evolutionary approaches for assessment of geo-hazard landslide susceptibility mappingGeomatics, Natural Hazards and Risk2019105

高被引文献

1. 1
   Air quality index prediction using IDW geostatistical technique and OLS-based GIS technique in Kuala Lumpur, MalaysiaGeomatics, Natural Hazards and Risk2019123
2. 2
   Potential of hybrid evolutionary approaches for assessment of geo-hazard landslide susceptibility mappingGeomatics, Natural Hazards and Risk2019105
3. 3
   Novel hybrids of adaptive neuro-fuzzy inference system (ANFIS) with several metaheuristic algorithms for spatial susceptibility assessment of seismic-induced landslideGeomatics, Natural Hazards and Risk201993
4. 4
   Water depth estimation from Sentinel-2 imagery using advanced machine learning methods and explainable artificial intelligenceGeomatics, Natural Hazards and Risk202335
5. 5
   Predicting PM2.5 levels over the north of Iraq using regression analysis and geographical information system (GIS) techniquesGeomatics, Natural Hazards and Risk202131
6. 6
   Two novel neural-evolutionary predictive techniques of dragonfly algorithm (DA) and biogeography-based optimization (BBO) for landslide susceptibility analysisGeomatics, Natural Hazards and Risk201923
7. 7
   Brief communication: Radar images for monitoring informal urban settlements in vulnerable zones in Lima, PeruNatural Hazards and Earth System Sciences202213
8. 8
   Evaluating the impact of land use/land cover and rainfall changes on regional soil erosionGeomatics, Natural Hazards and Risk20256
9. 9
   Landslide susceptibility mapping based on data mining models in Lesser Caucasus and Kura foreland basin (Armenia and Azerbaijan)Geomatics, Natural Hazards and Risk20252

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